Service Popularity-Based Smart Resources Partitioning for Fog Computing-Enabled Industrial Internet of Things

Gaolei Li*, Jun Wu, Jianhua Li, Kuan Wang, Tianpeng Ye

*この研究の対応する著者

研究成果: Article査読

100 被引用数 (Scopus)

抄録

Recently, fog computing has gained increasing attention in processing the computing tasks of the industrial Internet of things (IIoT) with different service popularity. In task-diversified fog computing-enabled IIoT (F-IIoT), the mismatch between expected computing efficiency and partitioned resources on fog nodes (FNs) may pose serious traffic congestion even large-scale industrial service interruptions. The existing works mainly studied offloading which type of computing tasks into FNs, but few studies enabled smart resource partitioning of FNs. In this paper, a service popularity-based smart resources partitioning (SPSRP) scheme is proposed for fog computing-enabled IIoT. We first exploit Zipf's law to model the relationship between popularity ranks and computing costs of IIoT services. Moreover, we propose an implementation architecture of the SPSRP scheme for F-IIoT, which decouples the computing control layer from data processing layer of IIoT through a specified SPSRP controller. Besides, a mobility and heterogeneity-Aware partitioning algorithm is presented for extending SPSRP scheme to seamlessly support cross-domain resources partitioning. The simulations demonstrate that the SPSRP scheme can bring notable performance improvements on delay time, successful response rate and fault tolerance for fog computing to deal with the large-scale IIoT services.

本文言語English
論文番号8377998
ページ(範囲)4702-4711
ページ数10
ジャーナルIEEE Transactions on Industrial Informatics
14
10
DOI
出版ステータスPublished - 2018 10月
外部発表はい

ASJC Scopus subject areas

  • 制御およびシステム工学
  • 情報システム
  • コンピュータ サイエンスの応用
  • 電子工学および電気工学

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